Performance Prediction and Evaluation in Female Handball Players Using Machine Learning Models

Player selection is one the most important tasks for any sport and handball is no exception. The performance of the players depends on various factors such as the opposition team, the venue, their current form etc. The analysis and prediction of players’ performance of specific athletic tasks have increasing importance in both game and training planning. 

Therefore, the use of effective machine learning models may contribute to the ability to achieve high accuracy predictions of players’ athletic performance. The aim of this study was to evaluate different Machine learning and Deep learning models for predicting particular types of athletic performance in female handball players and to determine the significant factors influencing predicted performances by using the superior model.

Keywords: Artificial Intelligence, Athletic Performance, Machine Learning Models, Radial-Basis Function Neural Network.